aiqbench analysis
This research demonstrates the application of advanced ontology alignment techniques—specifically using OWL reasoning and HermiT—to unify disparate UK and NATO defence data standards (IES, HQDM, BFO). By establishing a rigorous crosswalk between these critical infrastructure models, the work advances the Machine Learning field's ability to handle complex, high-stakes semantic interoperability in large-scale systems.
Consistency Is Not Coherence: Orientation Search for Certified Alignments Between 4D Defence Upper Ontologies
arXiv:2608.21914v1 Announce Type: new Abstract: We align three upper ontologies that sit under UK and NATO defence data infrastructure: the Information Exchange Standard (IES), the Higher Quality Data Model (HQDM) that underpins the National Digital Twin, and Basic Formal Ontology (BFO). No public alignment between IES and HQDM existed. Promoting a hand-curated 17-correspondence crosswalk to OWL and reasoning over the complete merged ontologies with HermiT produces three results that we believe matter beyond this pair.
Abstract:We align three upper ontologies that sit under UK and NATO defence data infrastructure: the Information Exchange Standard (IES), the Higher Quality Data Model (HQDM) that underpins the National Digital Twin, and Basic Formal Ontology (BFO). No public alignment between IES and HQDM existed. Promoting a hand-curated 17-correspondence crosswalk to OWL and reasoning over the complete merged ontologies with HermiT produces three results that we believe matter beyond this pair.
14 pages. Long paper accepted at the Ontology Matching 2026 workshop (OM 2026), co-located with ISWC 2026. Code and data: this https URL
Artificial Intelligence (cs.AI); Databases (cs.DB); Logic in Computer Science (cs.LO)
arXiv:2608.21914 [cs.AI]
(or arXiv:2608.21914v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2608.21914 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 194 words
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